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Benefits of physical and machine learning hybridization for photovoltaic power forecasting

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  1. Wang, Wenting & Guo, Yufeng & Yang, Dazhi & Zhang, Zili & Kleissl, Jan & van der Meer, Dennis & Yang, Guoming & Hong, Tao & Liu, Bai & Huang, Nantian & Mayer, Martin János, 2024. "Economics of physics-based solar forecasting in power system day-ahead scheduling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
  2. Mayer, Martin János & Yang, Dazhi, 2024. "Optimal place to apply post-processing in the deterministic photovoltaic power forecasting workflow," Applied Energy, Elsevier, vol. 371(C).
  3. Tatsuya Honda & Kenshin Takemura & Susumu Matsumae & Nobutomo Morita & Wataru Iwasaki & Ryoji Arita & Suguru Ueda & Yeoh Wen Liang & Osamu Fukuda & Kazuya Kikunaga & Shinya Ohmagari, 2024. "Quantification of caffeine in coffee cans using electrochemical measurements, machine learning, and boron-doped diamond electrodes," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-14, March.
  4. Mayer, Martin János & Yang, Dazhi & Szintai, Balázs, 2023. "Comparing global and regional downscaled NWP models for irradiance and photovoltaic power forecasting: ECMWF versus AROME," Applied Energy, Elsevier, vol. 352(C).
  5. Ali, Mumtaz & Prasad, Ramendra & Jamei, Mehdi & Malik, Anurag & Xiang, Yong & Abdulla, Shahab & Deo, Ravinesh C. & Farooque, Aitazaz A. & Labban, Abdulhaleem H., 2024. "Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks," Renewable Energy, Elsevier, vol. 221(C).
  6. Amedeo Buonanno & Giampaolo Caputo & Irena Balog & Salvatore Fabozzi & Giovanna Adinolfi & Francesco Pascarella & Gianni Leanza & Giorgio Graditi & Maria Valenti, 2024. "Machine Learning and Weather Model Combination for PV Production Forecasting," Energies, MDPI, vol. 17(9), pages 1-15, May.
  7. Tao, Kejun & Zhao, Jinghao & Tao, Ye & Qi, Qingqing & Tian, Yajun, 2024. "Operational day-ahead photovoltaic power forecasting based on transformer variant," Applied Energy, Elsevier, vol. 373(C).
  8. Mayer, Martin János & Yang, Dazhi, 2022. "Probabilistic photovoltaic power forecasting using a calibrated ensemble of model chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  9. Mayer, Martin János & Biró, Bence & Szücs, Botond & Aszódi, Attila, 2023. "Probabilistic modeling of future electricity systems with high renewable energy penetration using machine learning," Applied Energy, Elsevier, vol. 336(C).
  10. Mayer, Martin János & Yang, Dazhi, 2023. "Pairing ensemble numerical weather prediction with ensemble physical model chain for probabilistic photovoltaic power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
  11. Fan, Siyuan & Geng, Hua & Zhang, Hengqi & Yang, Dazhi & Mayer, Martin János, 2025. "Incorporation of dynamic soiling loss into the physical model chain of photovoltaic (PV) systems," Energy, Elsevier, vol. 324(C).
  12. Jiang, Chengcheng & Zhu, Qunzhi, 2023. "Evaluating the most significant input parameters for forecasting global solar radiation of different sequences based on Informer," Applied Energy, Elsevier, vol. 348(C).
  13. Sarmas, Elissaios & Spiliotis, Evangelos & Stamatopoulos, Efstathios & Marinakis, Vangelis & Doukas, Haris, 2023. "Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models," Renewable Energy, Elsevier, vol. 216(C).
  14. Pei, Jingyin & Dong, Yunxuan & Guo, Pinghui & Wu, Thomas & Hu, Jianming, 2024. "A Hybrid Dual Stream ProbSparse Self-Attention Network for spatial–temporal photovoltaic power forecasting," Energy, Elsevier, vol. 305(C).
  15. Cao, Yisheng & Liu, Gang & Luo, Donghua & Bavirisetti, Durga Prasad & Xiao, Gang, 2023. "Multi-timescale photovoltaic power forecasting using an improved Stacking ensemble algorithm based LSTM-Informer model," Energy, Elsevier, vol. 283(C).
  16. Li, Caixia & Xu, Yuanyuan & Xie, Minglang & Zhang, Pengfei & Zhang, Bohan & Xiao, Bo & Zhang, Sujun & Liu, Ziheng & Zhang, Wenjie & Hao, Xiaojing, 2025. "Assessing solar-to-PV power conversion models: Physical, ML, and hybrid approaches across diverse scales," Energy, Elsevier, vol. 323(C).
  17. Honglin Xue & Junwei Ma & Jianliang Zhang & Penghui Jin & Jian Wu & Feng Du, 2024. "Power Forecasting for Photovoltaic Microgrid Based on MultiScale CNN-LSTM Network Models," Energies, MDPI, vol. 17(16), pages 1-13, August.
  18. Adam Krechowicz & Maria Krechowicz & Katarzyna Poczeta, 2022. "Machine Learning Approaches to Predict Electricity Production from Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-41, December.
  19. Zhijian Hou & Yunhui Zhang & Xuemei Cheng & Xiaojiang Ye, 2025. "Photovoltaic Power Forecasting Based on Variational Mode Decomposition and Long Short-Term Memory Neural Network," Energies, MDPI, vol. 18(13), pages 1-28, July.
  20. Nunes Maciel, Joylan & Javier Gimenez Ledesma, Jorge & Hideo Ando Junior, Oswaldo, 2024. "Hybrid prediction method of solar irradiance applied to short-term photovoltaic energy generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  21. Li, Baojie & Chen, Xin & Jain, Anubhav, 2024. "Power modeling of degraded PV systems: Case studies using a dynamically updated physical model (PV-Pro)," Renewable Energy, Elsevier, vol. 236(C).
  22. Gao, Qi & Chen, Yun & Yang, Dazhi & Zhang, Hao & Yang, Guoming & Shen, Yanbo & Xia, Xiang’ao & Liu, Bai, 2025. "Firm power generation with photovoltaic overbuilding and pumped hydro storage," Energy, Elsevier, vol. 324(C).
  23. Chu, Yinghao & Yang, Dazhi & Yu, Hanxin & Zhao, Xin & Li, Mengying, 2024. "Can end-to-end data-driven models outperform traditional semi-physical models in separating 1-min irradiance?," Applied Energy, Elsevier, vol. 356(C).
  24. Choi, Jung & Son, Seok-Woo & Lee, Seungjik & Park, Sangdae, 2024. "Advancing global solar photovoltaic power forecasting with sub-seasonal climate outlooks," Renewable Energy, Elsevier, vol. 237(PC).
  25. Aristeidis Mystakidis & Paraskevas Koukaras & Nikolaos Tsalikidis & Dimosthenis Ioannidis & Christos Tjortjis, 2024. "Energy Forecasting: A Comprehensive Review of Techniques and Technologies," Energies, MDPI, vol. 17(7), pages 1-33, March.
  26. Zhang, Ruoyang & Wu, Yu & Zhang, Lei & Xu, Chongbin & Wang, ZeYu & Zhang, Yanfeng & Sun, Xiaomin & Zuo, Xin & Wu, Yuhan & Chen, Qian, 2025. "A multiscale network with mixed features and extended regional weather forecasts for predicting short-term photovoltaic power," Energy, Elsevier, vol. 318(C).
  27. Wang, J.L. & Yan, Ting & Tang, Xin & Pan, W.G., 2025. "Design and operation of hybrid ground source heat pump systems: A review," Energy, Elsevier, vol. 316(C).
  28. Mauro Tucci & Antonio Piazzi & Dimitri Thomopulos, 2024. "Machine Learning Models for Regional Photovoltaic Power Generation Forecasting with Limited Plant-Specific Data," Energies, MDPI, vol. 17(10), pages 1-21, May.
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